Habitat as a mediator of mesopredator‐driven mammal extinction

A prevailing view in dryland systems is that mammals are constrained by the scarcity of fertile soils and primary productivity. An alternative view is that predation is a primary driver of mammal assemblages, especially in Australia, where 2 introduced mesopredators—feral cat (Felis catus) and red fox (Vulpes vulpes)—are responsible for severe declines of dryland mammals. We evaluated productivity and predation as drivers of native mammal assemblage structure in dryland Australia. We used new data from 90 sites to examine the divers of extant mammal species richness and reconstructed historic mammal assemblages to determine proportional loss of mammal species across broad habitat types (landform and vegetation communities). Predation was supported as a major driver of extant mammal richness, but its effect was strongly mediated by habitat. Areas that were rugged or had dense grass cover supported more mammal species than the more productive and topographically simple areas. Twelve species in the critical weight range (CWR) (35–5500 g) that is most vulnerable to mesopredator predation were extirpated from the continent's central region, and the severity of loss of species correlated negatively with ruggedness and positively with productivity. Based on previous studies, we expect that habitat mediates predation from red foxes and feral cats because it affects these species’ densities and foraging efficiency. Large areas of rugged terrain provided vital refuge for Australian dryland mammals, and we predict such areas will support the persistence of CWR species in the face of ongoing mammal declines elsewhere in Australia.     

Exploring factors that shape small-scale farmers’ opinions on the adoption of eco-friendly nets for vegetable production

If agro-ecological systems are to realize their potential as sustainable alternatives to conventional agricultural systems, innovation diffusion needs to be enhanced. We conducted surveys among 214 small-scale vegetable farmers in Benin, a food-deficit country in West Africa, on how they perceived the different attributes of eco-friendly nets (EFNs). The nets act as physical barriers against insects in vegetable production and so reduce pesticide use. Understanding farmer perceptions about new technologies helps reveal farmers’ propensity to adopt them. Intensity of attitude was measured on a Likert scale, and an ordered probit model was used to determine which characteristics of nets were most influential. Eighteen percent of farmers thought that EFNs would benefit them, but almost half preferred not to adopt this technology at all. The main reason for rejecting the nets was the perceived high labor requirement, particularly on larger plots of land. This largely negative perception was strongest among farmers with large areas cultivated with vegetables, farmers who had little or no experience in a trial, and those living far from extension services. We recommend expanded trials that engage a higher proportion of farmers, strengthening of external support for those wanting to use the nets and further technological development to reduce labor costs, improved access to finance and increased education about the negative impacts of insecticides abuse.     

A framework for evaluating the impact of the IUCN Red List of threatened species

The International Union for Conservation of Nature (IUCN) Red List of Threatened Species, a species extinction risk assessment tool, has been guiding conservation efforts for over 5 decades. It is widely assumed to have been instrumental in preventing species from moving closer to extinction and driving recoveries. However, the impact of the IUCN Red List in guiding conservation has not been evaluated. We conducted, transcribed, and coded interviews with experts who use the IUCN Red List across a range of sectors to understand how the list is used in conservation. We developed a theory of change to illustrate how and why change is expected to occur along causal pathways contributing to the long-term goal of the IUCN Red List and an evaluation framework with indicators for measuring the impact of the IUCN Red List in generating scientific knowledge, raising awareness among stakeholders, designating priority conservation sites, allocating funding and resources, influencing development of legislation and policy, and guiding targeted conservation action (key themes). Red-list assessments were the primary input leading to outputs (scientific knowledge, raised awareness), outcomes (better informed priority setting, access to funding and resource availability, improved legislation and policy), and impact (implemented conservation action leading to positive change) that have resulted in achievement of IUCN Red List goals. To explore feasibility of attributing the difference made by the IUCN Red List across themes, we studied increased scientific knowledge, raised awareness, access to funding and resource allocation, and increased conservation activity. The feasibility exploration showed increased scientific knowledge over time identified through positive trends in publications referring to the IUCN Red List in the literature; raised awareness of the list following high IUCN activity identified by peaks in online search activity; an increased proportion of conservation funding bodies requesting IUCN Red List status in the application process; and, based on interviews with Amphibian Specialist Group members, red-list assessments were essential in connecting relevant stakeholders and ensuring conservation action. Although we identified the IUCN Red List as a vital tool in global conservation efforts, it was challenging to measure specific impacts because of its ubiquitous nature. We are the first to identify the influence of the IUCN Red List on conservation.     

Validation of an automated data collection method for quantifying social networks in collective behaviours

The social network of preferences among group members can affect the distribution and consequences of collective behaviours. However, the behavioural contexts and taxa in which social network structure has been described are still limited because such studies require extensive data. Here, we highlight the use of an automated passive integrated transponder (PIT)-tag monitoring system for social network analyses and do so in a novel context—nestling provisioning in an avian cooperative breeder, for which direct observation of social behaviours is difficult. First, we used observers and cameras to arrive at a suitable metric of nest visit synchrony in the PIT-tag data. Second, we validated the use of this metric for social network analyses using internal nest video cameras. Third, we used hierarchical regression models with ‘sociality’ parameter to investigate structure of networks collected from multiple groups. Use of PIT tags led to nest visitation duration and frequency being obtained with a high degree of accuracy for all group members, except for the breeding female for whom accurate estimations required the use of a video camera due to her high variability in visitation time. The PIT-tag dataset uncovered significant variability in social network structure. Our results highlight the importance of combining complementary observation methods when conducting social network analyses of wild animals. Our methods can also be generalised to multiple contexts in social systems wherever repeated encounters with other individuals in closed space have ecological implications.